Abstract:

Information Technologies are evolving faster than ever and students need to acquire programming skills early on in their education process to be able to keep up with these changes. Several authors have found that developing computational thinking skills enhances problem solving, critical thinking, and innovation abilities. This is the main reason for including at least one programming course in the freshman year of most STEM majors. It is, however, a challenge for students to learn to program, since it requires to achieve an abstract understanding of several computational concepts before being able to implement them in a concrete way to solve a particular problem. Applying theoretical programming concepts to solve an engineering problem using the computer has proven to be a very difficult endeavor, thus decreasing the interest, commitment, and overall motivation of students as the course progresses, causing high desertion or failure levels.

This project focuses on using robots as a tool for improving the students' experience while acquiring computational thinking skills. Other authors have concluded that the use of robots has a positive impact on thinking skills related to the following dimensions: sequences, correspondence, instruction-action and debugging. Besides, the use of a concrete physical tool fosters motivation and creativity, and encourages students to solve the tasks at hand and even propose their own activities.

Educational institutions in other countries have also studied the use of robots as a trigger for computational thinking development since the early stages of elementary education, however, in Mexico, this approach has not been widely exploited. In this proposal, the use of blocks-based programming for robots is intended to develop structured thinking for problem solving using a game-based approach. The main objective of the research was to improve academic performance and keep high levels of motivation in the classroom.

Academic performance was quantitatively measured through a practical test applied to 325 students that completed a course of basic programming for engineering majors. The test included an outline of the problems to be solved by coding a Python script. There was an experimental and a control group, and the inferential analysis of the results showed a significant difference between the academic performance of both groups. Based on these results we were not able to determine a positive correlation, however, we did notice several factors that affected our results, such as the course format (online vs face-to-face), the students’ major, the after effects of the pandemic, and at-home distractors. Furthermore, we perceived a decrease in the number of outliers representing students that failed the course. This is an interesting finding, and although we need to run more experiments, we believe that it could be a strong indicator of the absence of students with very low grades.

Motivation, on the other hand, was quantitatively measured through a survey proven to estimate the motivational climate in the classroom; it comprehends a set of items that measure the students’ satisfaction with each statement, using a Likert scale from 1 to 5. There was an experimental and a control group, and the inferential analysis of the results showed a significant difference in the measured curiosity stimuli between these groups.

Keywords:

Motivation, robots, STEM, intellectual curiosity, higher education.